> I'm sure that the deep learning folks will object: factorising in sub
> problemswas yesterday; now we ge end-to-end. And indeed there are a
> few examples where a field was swept by NN in short time (e.g.
> vision), at least in terms of accuracy. This was done not by
> factorising the problem better, but by solving it end-to-end with a
> lot of data.

most of the deep learning folks don't know what the hell they're doing
and it will cost us big time in the near or far future.
Just throwing data at a problem you do not understand will get you
better results but won't solve the fundamental issue of not
understanding it.